36 citations · 81 across the 11 of their papers we have counts for
17 papers · 1 filter
VAE Explainer: Supplement Learning Variational Autoencoders with Interactive Visualization
Donald Bertucci, Alex Endert
Variational Autoencoders are widespread in Machine Learning, but are typically explained with dense math notation or static code examples. This paper presents VAE Explainer, an int…
Left, Right, and Gender: Exploring Interaction Traces to Mitigate Human Biases
Emily Wall, Arpit Narechania, Adam Coscia +2
Human biases impact the way people analyze data and make decisions. Recent work has shown that some visualization designs can better support cognitive processes and mitigate cognit…
Lumos: Increasing Awareness of Analytic Behavior during Visual Data Analysis
Arpit Narechania, Adam Coscia, Emily Wall +1
Visual data analysis tools provide people with the agency and flexibility to explore data using a variety of interactive functionalities. However, this flexibility may introduce po…
Causal Perception in Question-Answering Systems
Po-Ming Law, Leo Yu-Ho Lo, Alex Endert +2
Root cause analysis is a common data analysis task. While question-answering systems enable people to easily articulate a why question (e.g., why students in Massachusetts have hig…
Toward a Bias-Aware Future for Mixed-Initiative Visual Analytics
Adam Coscia, Duen Horng Chau, Alex Endert
Mixed-initiative visual analytics systems incorporate well-established design principles that improve users' abilities to solve problems. As these systems consider whether to take…
A Comparative Analysis of Industry Human-AI Interaction Guidelines
Austin P. Wright, Zijie J. Wang, Haekyu Park +6
With the recent release of AI interaction guidelines from Apple, Google, and Microsoft, there is clearly interest in understanding the best practices in human-AI interaction. Howev…